cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Ronal Watrianthos
Contact Email
ronal.watrianthos@gmail.com
Phone
+6281263621335
Journal Mail Official
joseitjournal@gmail.com
Editorial Address
Professional Organization - Ikatan Ahli Informatika Indonesia (IAII) / Indonesian Informatics Experts Association Jalan Jati Padang Raya No. 41 Jati Padang Pasar Minggu 12540 South Jakarta - Indonesia http://iaii.or.id/
Location
Unknown,
Unknown
INDONESIA
Journal of Systems Engineering and Information Technology
Published by Organisasi Profesi IKATAN AHLI INFORMATIKA INDONESIA
ISSN : -     EISSN : 2829310X     DOI : https://doi.org/10.29207/joseit.*
Core Subject : Science,
Computer Science & IT
International Journal of Systems Engineering and Information Technology (JOSEIT) is an international journal published by Ikatan Ahli Informatika Indonesia (IAII / Association of Indonesian Informatics Experts). The research article submitted to this online journal will be peer-reviewed. The accepted research articles will be available online (free download) following the journal peer-reviewing process. The language used in this journal is English. JOSEIT is a peer-reviewed, blinded journal dedicated to publishing quality research results in Computers Engineering and Information Technology but is not limited implicitly. All journal articles can be read online for free without a subscription because all journals are open-access.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 5 Documents
 1 
Search results for , issue "Vol 2 No 2 (2023): September 2023" : 5 Documents clear
Monitoring System for Temperature and Humidity Sensors in the Production Room Using Node-Red as the Backend and Grafana as the Frontend Khoirul Anam; Difa Nur Rofi; Ruci Meiyanti
Journal of Systems Engineering and Information Technology (JOSEIT) Vol 2 No 2 (2023): September 2023
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/joseit.v2i2.5222

Abstract

The client from the TRIAS project is facing issues with a decrease in production quality or defective products. They require a monitoring system for temperature and humidity in the production area, providing real-time notifications in case of any anomalies in temperature and humidity. However, the project has a limited budget, which poses a challenge for the contractor in developing a monitoring system that tracks temperature and humidity changes using temperature and humidity sensors as the data source. It should also provide alarms if the temperature and humidity values exceed the standard values for the room. Additionally, the pricing offer should be adjusted using information technology. The research methodology used in this study includes qualitative methods such as observation, literature review, and interviews to gather data on the mentioned issues. The SWOT method is used to analyze business process problems, while the Waterfall method is employed for system development. Based on the research findings, the researcher concludes that this project requires cost reduction in material usage and also needs a data visualization application for the mentioned sensors. The visualization application system utilizes Grafana as the frontend, chosen for its high flexibility in processing. The temperature and humidity data obtained from the sensors will be recorded by Node-Red as the backend and synchronized on the server. The data stored on the server will be saved in a MySQL database. The data from the database will be synchronized with Grafana for processing and visualization, presenting the data in easily understandable graphical forms.
Acceleration and Clustering of Liver Disorder Using K-Means Clustering Method with Mahout’s Library Tariq bin Samer; Cahyo Darujati
Journal of Systems Engineering and Information Technology (JOSEIT) Vol 2 No 2 (2023): September 2023
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/joseit.v2i2.5334

Abstract

Evaluation of liver disorders was performed to observed and clustered in Big Data environment applications. However, since liver disorder is a common illness, global awareness of such cases can be life threatening, therefore the urge to avoid and study must be essential. The idea of parallel computing is established on the basis of the K-means method. The MapReduce framework is used to complete multi-node data processing, and a solution to the MapReduce K-Means method is given. The ultimate goal is to establish clusters that allow each entity to be examined and assigned to a certain cluster. These algorithms are designed to accelerate computations, reduce the volume of enormous data that must be computed, and improve the efficiency of arithmetic operations. The combination of theoretical analysis and experimental evaluation is very significant.
Performance Analysis of Mobile Ad-Hoc Networks Based on TCP and UDP Traffic on AODV Protocol for Warship Communication Alon Jala Tirta Segara; Afifah Dwi Ramadhani
Journal of Systems Engineering and Information Technology (JOSEIT) Vol 2 No 2 (2023): September 2023
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/joseit.v2i2.5343

Abstract

This research focuses on evaluating two key parameters in Mobile Ad-Hoc Networks (MANETs) that use the AODV protocol for warship communication, namely the packet delivery ratio (PDR) and end-to-end delay. PDR describes the percentage of data packets that successfully reach their destination without loss or damage during transmission. The study will analyze and compare PDR in MANETs with TCP and UDP traffic to understand the reliability and efficiency of the AODV protocol in data delivery. Furthermore, the research will also assess end-to-end delay, which measures the time it takes data packets to reach their final destination. Evaluating this delay will provide insights into the network's responsiveness in transmitting data between source and destination. The results of this research will offer valuable information about the performance of MANETs using the AODV protocol with TCP and UDP traffic. These findings can be used to optimize warship communication systems by selecting the most suitable protocol and traffic to achieve high PDR and minimal end-to-end delay; this study has the potential to serve as a critical foundation for developing reliable and efficient mobile ad hoc networks for military communication in dynamic and challenging environments.
Overview and Exploratory Analyses of CICIDS 2017 Intrusion Detection Dataset Akinyemi Oyelakin; Ameen A.O; Ogundele T.S; Salau-Ibrahim T; Abdulrauf U.T; Olufadi H.I; Ajiboye I.K; Muhammad-Thani S; Adeniji I. A
Journal of Systems Engineering and Information Technology (JOSEIT) Vol 2 No 2 (2023): September 2023
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/joseit.v2i2.5411

Abstract

Intrusion detection systems are used to detect attacks on a network. Machine learning (ML) approaches have been widely used to build such intrusion detection systems (IDSs) because they are more accurate when built from a very large and representative dataset. Recently, one of the benchmark datasets that are used to build ML-based intrusion detection models is the CICIDS2017 dataset. The data set is contained in eight groups and was collected from the Data Set & Repository of the Canadian Institute of Cyber Security. The data set is available in both PCAP and net flow formats. This study used the net flow records in the CIDIDS2017 dataset, as they were found to contain newer attacks, very large, and useful for traffic analysis. Exploratory data analysis (EDA) techniques were used to reveal various characteristics of the dataset. The general objective is to provide more insight into the nature, structure, and issues of the data set so as to identify the best ways to use it to achieve improved ML-based IDS models. Furthermore, some of the open problems that can arise from the use of the dataset in any machine learning-based intrusion detection systems are highlighted and possible solutions are briefly discussed. The EDA techniques used revealed important relationships between the input variables and the target class. The study concluded that the EDA can better influence the decision about future IDS research using the dataset.
An Optimal Solution to the Overfitting and Underfitting Problem of Healthcare Machine Learning Models Anil Kumar Prajapati Anil; Umesh Kumar Singh
Journal of Systems Engineering and Information Technology (JOSEIT) Vol 2 No 2 (2023): September 2023
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/joseit.v2i2.5460

Abstract

In the current technological era, artificial intelligence is becoming increasingly popular. Machine learning, as the branch of AI is taking charge in every field such as healthcare, the Stock market, Automation, Robotics, Image Processing, and so on. In the current scenario, machine learning and/or deep learning are becoming very popular in medical science for disease prediction. Much research is underway in the form of disease prediction models by machine learning. To ensure the performance and accuracy of the machine learning model, it is important to keep some basic things in mind during training. The machine learning model has several issues which must be rectified duration of the training of the model so that the learning model works efficiently such as model selection, parameter tuning, dataset splitting, cross-validation, bias-variance tradeoff, overfitting, underfitting, and so on. Under- and over-fitting are the two main issues that affect machine learning models. This research paper mainly focuses on minimizing and/or preventing the problem of overfitting and underfitting machine learning models.

Page 1 of 1 | Total Record : 5

 1 

Filter by Year

2023 2023


Reset
Filter By Issues
All Issue Vol 4 No 2 (2025): September 2025 Vol 4 No 1 (2025): April 2025 Vol 3 No 2 (2024): Sep 2024 Vol 3 No 1 (2024): March 2024 Vol 2 No 2 (2023): September 2023 Vol 2 No 1 (2023): March 2023 Vol 1 No 2 (2022): September 2022 Vol 1 No 1 (2022): March 2022